2019 Technical Track – Kristen M. Altenburger

Kristen M. Altenburger

Ph.D. Candidate, Computational Social Science
Stanford University

Technical Track – Ruffled Feathers: Trait Inference on Social Networks Beyond Homophily

Kristen M. AltenburgerKristen M. Altenburger is a PhD candidate in Computational Social Science in the Management Science & Engineering Department at Stanford University advised by Johan Ugander and is a member of the Social Algorithms Lab.

Her research interests include social network analysis, machine learning, and causal inference. Kristen received her BS in Mathematics from Ohio University in 2012 where she was also a Barry M. Goldwater Scholar, completed a research fellowship at Stanford Law School with Alison Morantz and Daniel E. Ho in 2012-2014, and received her AM in Statistics from Harvard University in 2015. She is also a 2016 recipient of a National Defense Science & Engineering Graduate Fellowship.

Kristen was previously a Member of Technical Staff in the Data Science and Cyber Analytics Department at Sandia National Laboratories and was a 2016 SPOT Award recipient based on her research. During the summer of 2017, she joined the Social Science & Algorithms team at Netflix for an internship analyzing word-of-mouth effects and other social signals.

Find Kristen on LinkedIn.